Expert advice from Karlheinz Zuerl and the key to success: AI competence center for hybrid teams instead of an AI pope alone

👨🏻 Karlheinz Zuerl, CEO of the German Technology & Engineering Corporation (GTEC), emphasizes the need to introduce artificial intelligence (AI) in hybrid teams. Zuerl explains that there is often a large discrepancy between top management's enthusiasm for AI and its actual acceptance in everyday operations. He points out that this gap can best be closed through collaboration between AI competence centers and specialist departments.

In view of the hype surrounding artificial intelligence, many companies are appointing a top-level AI manager in order to bring what is supposedly the most important topic of our time into the company. But Zuerl sees this as a mistake. He emphasizes that companies can only benefit from AI if it is introduced across the entire workforce. He gained these insights in his role as interim manager, a position for which he was nominated in 2024 by the Steinbeis Augsburg Business School and the interim manager community United Interim.

Karlheinz Zuerl describes the problem clearly: The process usually begins with management learning about new technological developments. This is followed by a phase in which teams present optimistic, but often contradictory, use cases to management. Driven by this enthusiasm but with no clear direction, responsibility is ultimately given to a person who is often overwhelmed.

🌟 AI competence center as a solution

Karlheinz Zuerl emphasizes that it is not enough to have a supposed AI pope at the top. Rather, in-depth knowledge of operational processes is required in order to be able to estimate in practice where AI is actually useful. In his opinion, AI management is usually too far removed from everyday operations. This not only applies to AI projects, but generally applies to the introduction of new technologies. However, the discrepancy between expectations and actual results is particularly large with AI.

As a solution, Zuerl suggests setting up an AI competence center where management and operational expertise are brought together. The operational AI headquarters provides the necessary platforms, data and governance, i.e. sets of rules for dealing with AI. The implementation in the various departments is then carried out by teams from the respective specialist area, who also bear responsibility for this process, he explains.

⚖️ Advantages of a hybrid approach or grandiose and small-minded burial

A hybrid approach to introducing AI brings decisive advantages. Through this, innovations are integrated into the organization on a broad front and become an integral part of everyday operations. In contrast, with the traditional top-down approach, there is a risk that projects will be grandly launched and meekly buried a few months or years later, leaving no significant trace in the organization. Often the “AI Pope” who is frustrated due to a lack of project progress leaves the company after a while, which disappoints the remaining employees and leads to long-lasting skepticism about future innovations.

Over the course of his decades of consulting and management work, Zuerl has noticed that the more often management and employees have to experience innovation projects failing, the greater the distrust of all new approaches becomes. These negative experiences would have fatal consequences for the company culture: Large parts of the workforce categorically reject changes in the company because they have seen too often how the Pope of today became the persona non grata of tomorrow. With a top-down introduction of AI, the risk of this scenario repeating is very high.

📣 Similar topics

• 🤖 The importance of AI competence centers in hybrid teams
• 🌐 Widespread adoption of AI: moving away from silo thinking
• 💡 Strengthen innovation culture through hybrid AI implementation
• ⚙️ AI in everyday operations: Success model competence center
• 📊 AI competence centers: Key to sustainable success
• 📈 Hybrid AI strategy: advantages and challenges
• 🔍 Why a central AI leader often fails
• 🏢 Integration of AI into everyday work: Practical tips
• 🚀 Advancing AI: The role of competence centers
• 💼 From above or on site: AI strategies in comparison

#️⃣ Hashtags: #ArtificialIntelligence #HybridTeams #Innovation Culture #Everyday Business #Competence Centers

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🏥🕶️ The following steps are recommended for the practical implementation of the hybrid approach:

1. 💡 Establishment of an AI competence center

This center should consist of experts who have both technical know-how and a deep understanding of company processes. The main task is to provide data platforms and rules for the use of AI.

2. 📚 Training and continuing education

The entire workforce should be trained on the fundamentals and applications of AI. The competence center can serve as a central contact point for workshops and training programs.

3. 🔍 Pilot projects in specialist departments

Instead of starting large-scale, risky projects, smaller pilot projects should first be carried out in the respective specialist departments. These projects should have clearly defined goals and measurable results in order to be able to concretely demonstrate the benefits of AI.

4. 🤝 Collaboration and communication

Close collaboration between the AI ​​competence center and the specialist departments is essential. Regular meetings and ongoing exchange promote understanding and acceptance of further technological implementations.

5. 📈 Monitoring and adjustment

Continuous monitoring of the AI ​​solutions introduced and the adjustment of strategies and processes based on the collected data and results are crucial for long-term success.

🚀 Success stories and challenges

A successful approach to introducing AI in hybrid teams can be seen in various industries. One example is the automotive industry, where significant increases in efficiency have been achieved through the use of AI in production planning and control. Technology experts worked closely with production managers to develop tailor-made applications that could be seamlessly integrated into existing processes.

Suitable for:

• AI & Digital Technologies: How traditional industrial companies remain competitive through artificial intelligence

The hybrid approach has also proven successful in the healthcare sector. In hospitals, AI specialists work with medical professionals to develop AI systems for diagnostics and patient monitoring. These systems help doctors and nurses work and improve patient care by providing real-time data and enabling accurate predictions.

Suitable for:

• AI & Smart Healthcare: Using artificial intelligence for better healthcare services and health diagnosis 4.0

However, there are also challenges that should not be underestimated:

📊 Data quality

The quality of the data used for AI applications is crucial for success. Companies must ensure that the data is clean, complete and up-to-date.

🔒 Security and privacy concerns

The use of AI always brings with it questions of data protection and data security. Companies must ensure that sensitive data is protected and complies with legal requirements.

🔄 Change management

The shift to an AI-powered organization requires careful management. The workforce must be involved in the change process and transparent communication is required to reduce fears and resistance.

🤖✨ Unleashing innovative potential: Hybrid teams and artificial intelligence

The introduction of artificial intelligence in hybrid teams significantly increases the chances of success of AI projects. By combining technical know-how and a deep understanding of company processes, tailor-made solutions can be developed that create real added value. The hybrid approach not only promotes the acceptance of new technologies, but also prevents the failure of innovation projects and thus contributes to a positive company culture.

📣 Similar topics

• 🤖 Establishment of modern AI competence centers
• 📚 Targeted training: The path to an AI-fit team
• 🚀 Pilot projects as a guarantee of success for AI implementation
• 🤝 Collaboration between specialist departments and AI experts
• 🔍 Continuous monitoring to optimize AI solutions
• 🚗 Success stories: AI in the automotive industry
• 🏥 AI in Healthcare: Collaborating for Better Care
• 📊 Data quality as the key to the success of AI applications
• 🛡️ AI security and privacy requirements
• 🔄 Change management: People are the focus of AI implementation

#️⃣ Hashtags: #AIImplementation #HybridTeams #Training #DataQuality #ChangeManagement

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